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You may search for courses meeting the criteria offered below. If a search results in too many courses, add criteria or select a more narrow category. If you searched only by department and term, cross-listed courses will be displayed at the bottom of the list.

    COURSE CATALOG SEARCH RESULTS

    19 courses found for the selected term.
    Click on a course title for more information.
    Click on a department code to view complete departmental listings.
    If you searched only by department and term, cross-listed courses will be displayed at the bottom of the list.


  • Credits: 4Max Enrollment: 999
    Course Type: LectureSection Enrollment: 22
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W 1:20 PM-2:35 PM / STODRD G2

    Same as CSC 109. The world is growing increasingly reliant on collecting and analyzing information to help people make decisions. Because of this, the ability to communicate effectively about data is an important component of future job prospects across nearly all disciplines. In this course, students learn the foundations of information visualization and sharpen their skills in communicating using data. Throughout the semester, we explore concepts in decision-making, human perception, color theory and storytelling as they apply to data-driven communication. Whether you’re an aspiring data scientist or you just want to learn new ways of presenting information, this course helps you build a strong foundation in how to talk to people about data.  {M}
    Linked Course: No
    CSC Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 40
    Course Type: LectureSection Enrollment: 39
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W F 10:50 AM-12:05 PM / SAB-RD 220

    An introduction to data science using Python, R and SQL. Students learn how to scrape, process and clean data from the web; manipulate data in a variety of formats; contextualize variation in data; construct point and interval estimates using resampling techniques; visualize multidimensional data; design accurate, clear and appropriate data graphics; create data maps and perform basic spatial analysis; and query large relational databases. No prerequisites, but a willingness to write code is necessary. {M}
    Linked Course: No
    CSC Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 40
    Course Type: LectureSection Enrollment: 27
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W F 1:20 PM-2:35 PM / SAB-RD 220

    An introduction to data science using Python, R and SQL. Students learn how to scrape, process and clean data from the web; manipulate data in a variety of formats; contextualize variation in data; construct point and interval estimates using resampling techniques; visualize multidimensional data; design accurate, clear and appropriate data graphics; create data maps and perform basic spatial analysis; and query large relational databases. No prerequisites, but a willingness to write code is necessary. {M}
    Linked Course: No
    CSC Crosslist
    View Textbook Information

  • Credits: 5Max Enrollment: 40
    Course Type: LectureSection Enrollment: 15
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W F 9:25 AM-10:40 AM / SAB-RD 301

    Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basic requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: MTH 201/ PSY 201, GOV 190, ECO 220, MTH 219, MTH 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist
    View Textbook Information

  • Credits: 5Max Enrollment: 40
    Course Type: LectureSection Enrollment: 15
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W F 10:50 AM-12:05 PM / SAB-RD 301

    Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basic requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: MTH 201/ PSY 201, GOV 190, ECO 220, MTH 219, MTH 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist
    View Textbook Information

  • Credits: 5Max Enrollment: 40
    Course Type: LectureSection Enrollment: 17
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W F 2:45 PM-4:00 PM / SAB-RD 301

    Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basic requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: MTH 201/ PSY 201, GOV 190, ECO 220, MTH 219, MTH 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 7
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: Th 1:20 PM-2:35 PM / SAB-RD 301

    Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basic requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: MTH 201/ PSY 201, GOV 190, ECO 220, MTH 219, MTH 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 8
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: Th 2:45 PM-4:00 PM / SAB-RD 301

    Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basic requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: MTH 201/ PSY 201, GOV 190, ECO 220, MTH 219, MTH 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 11
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: W 1:20 PM-2:35 PM / SEELYE 212

    Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basic requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: MTH 201/ PSY 201, GOV 190, ECO 220, MTH 219, MTH 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 4
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: W 2:45 PM-4:00 PM / SEELYE 212

    Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basic requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: MTH 201/ PSY 201, GOV 190, ECO 220, MTH 219, MTH 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 9
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T 1:20 PM-2:35 PM / SAB-RD 301

    Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basic requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: MTH 201/ PSY 201, GOV 190, ECO 220, MTH 219, MTH 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 8
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T 2:45 PM-4:00 PM / SAB-RD 301

    Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basic requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: MTH 201/ PSY 201, GOV 190, ECO 220, MTH 219, MTH 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 999
    Course Type: LectureSection Enrollment: 5
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T Th 9:25 AM-10:40 AM / BURTON 301

    Same as MTH 246. An introduction to probability, including combinatorial probability, random variables, discrete and continuous distributions. Prerequisites: MTH 153 and MTH 212 (may be taken concurrently), or permission of the instructor. {M}
    Linked Course: No
    MTH Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 30
    Course Type: LectureSection Enrollment: 17
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T Th 9:25 AM-10:40 AM / SAB-RD 301

    Same as MTH 291. Formerly MTH 247. Theory and applications of regression techniques; linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Prerequisite: one of the following: MTH 201/PSY 201, GOV 190, MTH 219, MTH 220, ECO 220, or the equivalent or a score of 4 or 5 on the AP Statistics examination. Enrollment limited to 30. {M}{N}
    Linked Course: No
    MTH Crosslist, PSY Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 30
    Course Type: LectureSection Enrollment: 10
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T Th 10:50 AM-12:05 PM / SAB-RD 301

    Same as MTH 291. Formerly MTH 247. Theory and applications of regression techniques; linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Prerequisite: one of the following: MTH 201/PSY 201, GOV 190, MTH 219, MTH 220, ECO 220, or the equivalent or a score of 4 or 5 on the AP Statistics examination. Enrollment limited to 30. {M}{N}
    Linked Course: No
    MTH Crosslist, PSY Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 16
    Course Type: SeminarSection Enrollment: 10
    Waitlist Count: 0
    Approval: Instructor PermissionReserved Seats: No
    Time/Location: M W 1:20 PM-2:35 PM / BASS 002

    Research on intergroup relationships and an exploration of theoretical and statistical models used to study mixed interpersonal interactions. Example research projects include examining the consequences of sexual objectification for both women and men, empathetic accuracy in interracial interactions, and gender inequality in household labor. A variety of skills including, but not limited to, literature review, research design, data collection, measurement evaluation, advanced data analysis, and scientific writing will be developed. Prerequisites: PSY 201, SDS 201, SDS 220 or equivalent and PSY 202. {M}{N}{S}
    Linked Course: NoRestriction(s): Limited to juniors and seniors
    PSY Crosslist, SWG Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 999
    Course Type: LectureSection Enrollment: 10
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T Th 10:50 AM-12:05 PM / BURTON 302

    Topics in statistics and data science. Statistical methods for analyzing data must be chosen appropriately based on the type and structure of the data being analyzed. The particular methods and types of data studied this in this course vary, but topics may include: categorical data analysis, time series analysis, survival analysis, structural equation modeling, survey methodology, Bayesian methods, resampling methods, spatial statistics, missing data methods, advanced linear models, statistical/machine learning, network science, relational databases, web scraping and text mining. This course may be repeated for credit with different topics. Prerequisites: MTH/SDS 290 or MTH/SDS 291 or MTH/SDS 292.  

    Theory and applications of statistical methods for the analysis of categorical data. The course includes an overview of statistical methods for analyzing discrete data including binary, multinomial, and count response variables. Nominal and ordinal responses will be considered. Topics may include contingency table and chi-squared analyses, logistic, Poisson, and negative-binomial regression models. R statistical software will be used. Prerequisites: Regression Analysis (MTH 291), Research Design (MTH 290), or Data Science (MTH 292), or permission of the instructor. 
    Linked Course: No
    View Textbook Information

  • Credits: 4Max Enrollment: 999
    Course Type: LectureSection Enrollment: 24
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W 10:50 AM-12:05 PM / BASS 002

    Topics in statistics and data science. Statistical methods for analyzing data must be chosen appropriately based on the type and structure of the data being analyzed. The particular methods and types of data studied this in this course vary, but topics may include: categorical data analysis, time series analysis, survival analysis, structural equation modeling, survey methodology, Bayesian methods, resampling methods, spatial statistics, missing data methods, advanced linear models, statistical/machine learning, network science, relational databases, web scraping and text mining. This course may be repeated for credit with different topics. Prerequisites: MTH/SDS 290 or MTH/SDS 291 or MTH/SDS 292.  

    Advanced programming techniques for data science using R. This course is not about data analysis---rather, students will learn the R programming language at a deep level. Topics may include data structures, control flow, regular expressions, functions, environments, functional programming, object-oriented programming, debuggging, testing, version control, documentation, literate programming, code review, and package development. The major goal for the course is to contribute to a viable, collaborative, open-source, publishable R package. Prereqs: SDS 192 and CSC 111. (E) 
    Linked Course: No
    Enforced Prereq(s): SDS 192 AND CSC 111
    View Textbook Information

  • Credits: 4Max Enrollment: 12
    Course Type: SeminarSection Enrollment: 18
    Waitlist Count: 0
    Approval: Instructor PermissionReserved Seats: No
    Time/Location: T Th 1:20 PM-2:35 PM / BASS 002

    This one-semester course leverages students’ previous coursework to address a real-world data analysis problem. Students collaborate in teams on projects sponsored by academia, government, and/or industry. Professional skills developed include: ethics, project management, collaborative software development, documentation, and consulting. Regular team meetings, weekly progress reports, interim and final reports, and multiple presentations are required. Open only to majors. Prerequisites: SDS 192, SDS 291 and CSC 111.  {M}
    Linked Course: NoRestriction(s): Limited to SDS majors AND Not open to first-years and sophomores
    View Textbook Information
  • 24 cross listed courses found for the selected term.


  • Credits: 4Max Enrollment: 999
    Course Type: LectureSection Enrollment: 45
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T Th 9:25 AM-10:40 AM / MCCONN 103

    Evolution frames much of biology by providing insights into how and why things change over time. For example, the study of evolution is essential to: understanding transitions in biodiversity across time and space, elucidating patterns of genetic variation within and between populations, and developing both vaccines and treatments for human diseases. Topics in this course include population genetics, molecular evolution, speciation, phylogenetics and macroevolution. Prerequisite: BIO 130 or BIO 132 or permission of the instructor. {N}
    Linked Course: No
    SDS Crosslist
    View Textbook Information

  • Credits: 3Max Enrollment: 999
    Course Type: LectureSection Enrollment: 30
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W 1:20 PM-2:35 PM / FORD 240

    This course focuses on methods and approaches in the emerging fields of bioinformatics and molecular evolution. Topics include the quantitative examination of genetic variation; selective and stochastic forces shaping proteins and catalytic RNA; data mining; comparative analysis of whole genome data sets; comparative genomics and bioinformatics; and hypothesis testing in computational biology. We explore the role of bioinformatics and comparative methods in the fields of molecular medicine, drug design, and in systematic, conservation and population biology. Prerequisite: BIO 132, or BIO 230, or BIO 232, or permission of the instructor. Laboratory (BIO 335) is strongly recommended but not required. {N}
    Linked Course: No
    SDS Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 999
    Course Type: LectureSection Enrollment: 14
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W 1:20 PM-2:35 PM / STODRD G2

    Same as SDS 109. The world is growing increasingly reliant on collecting and analyzing information to help people make decisions. Because of this, the ability to communicate effectively about data is an important component of future job prospects across nearly all disciplines. In this course, students learn the foundations of information visualization and sharpen their skills in communicating using data. Throughout the semester, we explore concepts in decision-making, human perception, color theory and storytelling as they apply to data-driven communication. Whether you’re an aspiring data scientist or you just want to learn new ways of presenting information, this course helps you build a strong foundation in how to talk to people about data.  {M}
    Linked Course: No
    SDS Crosslist
    View Textbook Information

  • Credits: 5Max Enrollment: 55
    Course Type: LectureSection Enrollment: 14
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W 9:25 AM-10:40 AM / MCCONN B15

    Summarizing, interpreting and analyzing empirical data. Attention to descriptive statistics and statistical inference. Topics include elementary sampling, probability, sampling distributions, estimation, hypothesis testing and regression. Assignments include use of statistical software and micro computers to analyze labor market and other economic data. Prerequisite: ECO 150 or ECO 153. Students are not given credit for both ECO 220 and any of the following courses: GOV 190, SOC 201, MTH 201, PSY 201 MTH 220. Course limited to 55 students. {M}{S}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 27
    Course Type: LabSection Enrollment: 12
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: F 9:25 AM-10:40 AM / BASS 103

    Summarizing, interpreting and analyzing empirical data. Attention to descriptive statistics and statistical inference. Topics include elementary sampling, probability, sampling distributions, estimation, hypothesis testing and regression. Assignments include use of statistical software and micro computers to analyze labor market and other economic data. Prerequisite: ECO 150 or ECO 153. Students are not given credit for both ECO 220 and any of the following courses: GOV 190, SOC 201, MTH 201, PSY 201 MTH 220. Course limited to 55 students. {M}{S}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 18
    Course Type: LabSection Enrollment: 2
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: F 10:50 AM-12:05 PM / BASS 103

    Summarizing, interpreting and analyzing empirical data. Attention to descriptive statistics and statistical inference. Topics include elementary sampling, probability, sampling distributions, estimation, hypothesis testing and regression. Assignments include use of statistical software and micro computers to analyze labor market and other economic data. Prerequisite: ECO 150 or ECO 153. Students are not given credit for both ECO 220 and any of the following courses: GOV 190, SOC 201, MTH 201, PSY 201 MTH 220. Course limited to 55 students. {M}{S}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 999
    Course Type: LectureSection Enrollment: 30
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T Th 2:45 PM-4:00 PM / STODRD G2

    Applied regression analysis. The specification and estimation of economic models, hypothesis testing, statistical significance, interpretation of results, policy implications. Emphasis on practical applications and cross-section data analysis. Prerequisites: ECO 150, ECO 153, MTH 111 and either ECO 220, MTH 220 or MTH 291. {M}{S}
    Linked Course: No
    SDS Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 12
    Course Type: SeminarSection Enrollment: 11
    Waitlist Count: 0
    Approval: Instructor PermissionReserved Seats: No
    Time/Location: Th 1:20 PM-4:00 PM / SEELYE 212

    Topics course. 

    An examination of selected topics related to American political behavior. Themes include empirical analysis, partisanship, voting behavior and turnout, public opinion and racial attitudes. Student projects involve analysis of survey data. {S}
    Linked Course: NoRestriction(s): Not open to first-years and sophomores
    SDS Crosslist
    View Textbook Information

  • Credits: 5Max Enrollment: 40
    Course Type: LectureSection Enrollment: 26
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W F 9:25 AM-10:40 AM / SAB-RD 301

    Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, GOV 190, ECO 220, MTH/SDS 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 5Max Enrollment: 40
    Course Type: LectureSection Enrollment: 23
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W F 10:50 AM-12:05 PM / SAB-RD 301

    Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, GOV 190, ECO 220, MTH/SDS 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 5Max Enrollment: 40
    Course Type: LectureSection Enrollment: 20
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W F 2:45 PM-4:00 PM / SAB-RD 301

    Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, GOV 190, ECO 220, MTH/SDS 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 14
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: Th 1:20 PM-2:35 PM / SAB-RD 301

    Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, GOV 190, ECO 220, MTH/SDS 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 12
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: Th 2:45 PM-4:00 PM / SAB-RD 301

    Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, GOV 190, ECO 220, MTH/SDS 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 9
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: W 1:20 PM-2:35 PM / SEELYE 212

    Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, GOV 190, ECO 220, MTH/SDS 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 14
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: W 2:45 PM-4:00 PM / SEELYE 212

    Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, GOV 190, ECO 220, MTH/SDS 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 11
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T 1:20 PM-2:35 PM / SAB-RD 301

    Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, GOV 190, ECO 220, MTH/SDS 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 9
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T 2:45 PM-4:00 PM / SAB-RD 301

    Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, GOV 190, ECO 220, MTH/SDS 220 or SOC 201. Exceptions may be allowed in special circumstances and require the permission of the adviser and the instructor. Prerequisite: MTH 111 or the equivalent, or permission of the instructor. Lab sections limited to 20. {M}
    Linked Course: Yes
    ENV Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 999
    Course Type: LectureSection Enrollment: 24
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T Th 9:25 AM-10:40 AM / BURTON 301

    Same as SDS 246. An introduction to probability, including combinatorial probability, random variables, discrete and continuous distributions. Prerequisites: MTH 153 and MTH 212 (may be taken concurrently), or permission of the instructor. {M}
    Linked Course: No
    SDS Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 30
    Course Type: LectureSection Enrollment: 10
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T Th 9:25 AM-10:40 AM / SAB-RD 301

    Same as SDS 291. Theory and applications of regression techniques; linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Prerequisite: one of the following: PSY 201, GOV 190, MTH 220, ECO 220, or the equivalent or a score of 4 or 5 on the AP Statistics examination. Enrollment limited to 25. {M}{N}
    Linked Course: No
    PSY Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 30
    Course Type: LectureSection Enrollment: 13
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: T Th 10:50 AM-12:05 PM / SAB-RD 301

    Same as SDS 291. Theory and applications of regression techniques; linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Prerequisite: one of the following: PSY 201, GOV 190, MTH 220, ECO 220, or the equivalent or a score of 4 or 5 on the AP Statistics examination. Enrollment limited to 25. {M}{N}
    Linked Course: No
    PSY Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 5Max Enrollment: 40
    Course Type: LectureSection Enrollment: 20
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: M W F 1:20 PM-2:35 PM / MCCONN 404

    An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data are discussed. Applications are emphasized, and students use R and other statistical software for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data. This course satisfies the basis requirement for the psychology major. Students who have taken MTH 111 or the equivalent or who have taken AP STAT should take SDS 220, which also satisfies the major requirement. Enrollment is restricted to psychology majors or permission of instructor. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, ECO 220, GOV 190, SDS 220, SDS 201,SOC  {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist, NSC Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 9
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: Th 1:20 PM-2:35 PM / BASS 103

    An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data are discussed. Applications are emphasized, and students use R and other statistical software for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data. This course satisfies the basis requirement for the psychology major. Students who have taken MTH 111 or the equivalent or who have taken AP STAT should take SDS 220, which also satisfies the major requirement. Enrollment is restricted to psychology majors or permission of instructor. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, ECO 220, GOV 190, SDS 220, SDS 201,SOC  {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist, NSC Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 0Max Enrollment: 20
    Course Type: LabSection Enrollment: 11
    Waitlist Count: 0
    Reserved Seats: No
    Time/Location: Th 2:45 PM-4:00 PM / BASS 103

    An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data are discussed. Applications are emphasized, and students use R and other statistical software for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data. This course satisfies the basis requirement for the psychology major. Students who have taken MTH 111 or the equivalent or who have taken AP STAT should take SDS 220, which also satisfies the major requirement. Enrollment is restricted to psychology majors or permission of instructor. Normally students receive credit for only one of the following introductory statistics courses: PSY 201, ECO 220, GOV 190, SDS 220, SDS 201,SOC  {M}
    Linked Course: Yes
    ENV Crosslist, MTH Crosslist, NSC Crosslist, SDS Crosslist
    View Textbook Information

  • Credits: 4Max Enrollment: 16
    Course Type: SeminarSection Enrollment: 9
    Waitlist Count: 0
    Approval: Instructor PermissionReserved Seats: No
    Time/Location: M W 1:20 PM-2:35 PM / BASS 002

    {M}{N}{S}
    Linked Course: NoRestriction(s): Limited to juniors and seniors
    SDS Crosslist
    View Textbook Information

The data in the course catalog are refreshed daily. Information concerning current and future course offerings is posted as it becomes available and is subject to change.

Smith College reserves the right to make changes to all announcements in the online Smith College Catalog Database, including changes in its course offerings, instructors, requirements for the majors and minors, and degree requirements. Course information contained herein is compiled and updated at regularly scheduled intervals by the Office of the Provost/Dean of the Faculty from data submitted by departments and programs. All data listed are as officially and formally approved by the Office of the Provost/Dean of the Faculty, the Committee on Academic Priorities and the faculty-at-large.